DEMETRA +
by Eurostat and National Bank of
Belgium
In case of any problems or questions, please contact Eurostat Unit B2 Methodology and Research at: estat-methodology@ec.europa.eu
To download documentation about Demetra+ from CROS portal please click here
Reference page to ESS guidelines on Seasonal adjustment here
For info about the next ESTP course on DEMETRA+ for beginners and advanced users that will be held at Eurostat please consult here
Description
Seasonal adjustment is an important step of the official statistics business
architecture and harmonisation of practices has proved to be key element of
quality of the output. In this spirit, since the 90s, Eurostat has been playing
a role in the promotion, development and maintenance of a software solution
(Demetra) freely available for seasonal adjustment in line with established
best practices.
In 2008, ESS (European Statistical System) guidelines on SA have been
endorsed by the CMFB and the SPC as a framework for seasonal adjustment of
PEEIs and other ESS and ESCB economic indicators. ESS guidelines cover all the
key steps of the seasonal and calendar adjustment process and represent an
important step towards the harmonisation of seasonal and calendar adjustment
practices within the ESS and in Eurostat. A common policy for the seasonal and
calendar adjustment of all infra-annual statistics will improve the quality and
comparability of the national data as well as enhance the overall quality of
European to the extent that proper SA tools exist and are available.
The SA Steering Group (the Eurostat-ECB high level group of experts from
NSIs and NCBs which has produced the ESS Guidelines for seasonal adjustment) is
promoting the development of a flexible software solution for SA to be used
within the ESS. The group has drawn its attention on the object oriented
technologies used by the R&D Unit of the Department of Statistics of the
National Bank of Belgium to develop a series of prototype tools for SA. This
has been considered as an adequate framework for the cooperative development of
a new generation of sustainable SA tools, enabling the implementation of the
ESS guidelines and replacing the previous Demetra whose maintenance and
sustainability is put in question.
Demetra+ is a family of modules
on seasonal adjustment, which are based on the two leading algorithms in that
domain (TRAMO&SEATS@ / X-12-ARIMA). TRAMO&SEATS@ (TRAMO \"Time
series Regression with ARIMA noise, Missing values and Outliers\", and
SEATS, \"Signal Extraction in ARIMA Time Series\", developed by Agustín Maravall and Victor Gómez)
and X-12-ARIMA (developed by David Findley and Brian Monsell)
are two different methods to seasonally adjust a time series. Both methods can
be divided into two main parts: a pre-adjustment step, which removes the
\"deterministic\" component of the series by means of a regression
model with Arima noises and the decomposition part itself. The two methods use
a very similar approach in the first part of the processing but they differ
completely in the decomposition part. Their comparison is often difficult, even
for the modelling step. More especially, their diagnostics focus on different
aspects and their outputs take completely different forms. One of the main
features of Demetra+ is to normalize - as much as possible - the different methods.
It tries to improve the comparability of the two methods by using as much as
possible, a common set of diagnostics and of presentation tools. That
fundamental choice implies that a number of routines of both methods have been
re-written in Demetra+. That can lead, compared to the
original programs, to small discrepancies in diagnostics or in peripheral
information that should not alter the general \"message\" provided by
the algorithms. Under no circumstances should the main results of the
original programs (seasonally adjusted series...) be impacted by that solution.
Features
The technology (Object Oriented components) underlying the toolkit has
proved to be a powerful and flexible solution for managing the complexity of
seasonal adjustment algorithms and integrating the major well-known SA engines
provided by the Bank of Spain and USCB. In addition, it could easily be
embedded in many different environments allowing fast developments and
extensions.
Future plans
JAVA version (now available here )